Life history strategies of stream fishes linked to predictors of hydrologic stability

Abstract Life history theory provides a framework to understand environmental change based on species strategies for survival and reproduction under stable, cyclical, or stochastic environmental conditions. We evaluated environmental predictors of fish life history strategies in 20 streams intersecting a national park within the Potomac River basin in eastern North America. We sampled stream sites during 2018–2019 and collected 3801 individuals representing 51 species within 10 taxonomic families. We quantified life history strategies for species from their coordinates in an ordination space defined by trade‐offs in spawning season duration, fecundity, and parental care characteristic of opportunistic, periodic, and equilibrium strategies. Our analysis revealed important environmental predictors: Abundance of opportunistic strategists increased with low‐permeability soils that produce flashy runoff dynamics and decreased with karst terrain (carbonate bedrock) where groundwater inputs stabilize stream flow and temperature. Conversely, abundance of equilibrium strategists increased in karst terrain indicating a response to more stable environmental conditions. Our study indicated that fish community responses to groundwater and runoff processes may be explained by species traits for survival and reproduction. Our findings also suggest the utility of life history theory for understanding ecological responses to destabilized environmental conditions under global climate change.

plants (Schaffer, 1974). Life history theory provides a fundamental framework to understand environmental change based on species strategies for survival and reproduction under stable, cyclical, or stochastic environmental conditions.
Fishes constitute an important model for life history research because they occupy diverse environmental conditions and have been undergoing natural selection since the Cambrian Period, longer than any other vertebrate group (Long et al., 2019). Freshwater and marine fishes exhibit life history strategies within a trilateral continuum defined by opportunistic, periodic, and equilibrium endpoints (Heino et al., 2013;Mims et al., 2010;Winemiller, 1992;Winemiller & Rose, 1992). Opportunistic strategies are demonstrated by shortlived, small-bodied species with early maturation, and low juvenile survivorship rates. Species that exhibit periodic strategies invest in growth and fecundity through delayed reproduction, whereas species exhibiting equilibrium strategies exhibit low fecundity but compensate for this with increased juvenile survivorship through parental care. Although some fish species exemplify a single life history strategy, most exhibit intermediate strategies between opportunistic, periodic, and equilibrium endpoints King & McFarlane, 2003;Winemiller & Rose, 1992). For example, fish species in the genus Etheostoma (Percidae) can exhibit early maturation as well as parental care (Frimpong & Angermeier, 2009;Winemiller & Rose, 1992), thus combining attributes of opportunistic and equilibrium strategies.
Life history theory has utility for understanding hydrologic controls on freshwater fish populations and communities. In lotic environments, flow regulation from dams and reservoirs can increase abundance of equilibrium strategist fishes (Kominoski et al., 2018; McManamay Mims & Olden, 2013;Olden et al., 2006;Perkin et al., 2017), whereas hydrologic spates and droughts can increase abundance of opportunistic strategists Magoulick et al., 2021;Malone et al., 2021;Mims & Olden, 2013;Olden & Kennard, 2010). Strong seasonal fluctuations in flow, such as seasonal inundation of floodplains, are associated with periodic strategist fishes (Tedesco et al., 2008). Spatial patterns also indicate the importance of hydrologic controls on fish life history diversity: Species found in flashy headwater streams tend to have smaller bodies, shorter lifespans, and earlier maturation than species found in more stable conditions downstream (Schlosser, 1990).
Similarly, large-bodied, long-lived fishes are more abundant where pool habitats are common and less abundant where turbulent riffle habitats are prevalent (Lamouroux et al., 2002).
Life history theory can also inform an ecological understanding of land use and climate change. Extreme precipitation events have increased over recent decades (Easterling et al., 2000;Gershunov et al., 2019), and many river systems show increasing flow variation in response (Coumou & Rahmstorf, 2012;Milly et al., 2008; Rahmstorf & Coumou, 2011;Ward et al., 2015). Urbanization can also increase flashiness and decrease stability of downstream flows (Anderson, 1970;O'Driscoll et al., 2010;Sauer et al., 1983), and therefore, cumulative effects of land use and climate change are expected to increase flow variation and decrease predictability of annual flow regimes (Miller & Hutchins, 2017;Zhou et al., 2016).
For instance, fish community composition can transition sharply where karst groundwater enters a stream (Coulter & Galarowicz, 2015), and temporal stability of stream fish communities has been attributed to the stabilizing effects of karstic groundwater inputs (Kollaus et al., 2015;Magoulick et al., 2021).
In this study, we applied life history theory to evaluate the role of hydrologic stability on stream fish community composition in the Potomac River basin of eastern North America. We tested our expectations that anthropogenic land use and flashy stream flows benefit species with opportunistic life history strategies rather than equilibrium or periodic strategies because species with rapid development and extended spawning seasons can rebound quickly from environmental disturbances. We also hypothesized that groundwater inputs increase equilibrium life history strategies due to stabilized hydrologic conditions that benefit investment in parental care for juvenile survival.

| Study area and sampling design
Our study area encompassed streams intersecting the Chesapeake and Ohio Canal National Historical Park (C&O Canal), an administrative unit of the U.S. National Park Service located in the headwaters of the Chesapeake Bay in eastern North America (Figure 1). A primary management objective of the National Park Service and the C&O Canal is to support biological conservation and diverse natural ecosystems (NPS, 2006). The C&O Canal extends for nearly 300 km along the north bank of the Potomac River and is characterized as a narrow band of forest within watersheds of mixed forest, agricultural, and urban land cover. The study area extends through three physiographic regions (Ridge and Valley, Blue Ridge, and Piedmont) and includes areas of karst geology within the Ridge and Valley province Weary & Doctor, 2014). Karst groundwater flow paths in this region exhibit spatially and temporally complex patterns typically associated with faults and fractured rock layers (Evaldi et al., 2009;Kozar et al., 1991) rather than conduit-type flow paths characteristic of cave systems.
We selected 20 streams from across the length of the C&O Canal that represented each physiographic region ( Figure 1; Table   A1 in Appendix 1). We sampled stream sites during baseflow conditions between June and September of 2018 (n = 9) and 2019 (n = 11). We identified 75-m sample reaches at each site and used two-pass backpack electrofishing techniques (Smith-Root LR24) with one electrofishing unit for each 3-4 m of stream width (Heimbuch et al., 1997). Fishes captured during each pass were placed in live wells, counted, identified to species, and returned to the stream. Fish unable to be identified in situ were euthanized with tricaine methanesulfonate and transported to the laboratory for identification. We estimated fish species abundance as the sum from the two electrofishing passes for each site. Fish were collected following U.S. National Park Service IACUC-approved standard operating procedures.

| Quantifying life history strategies
We compiled data on species life history traits to account for major sources of variation observed across North American freshwater fishes (Mims et al., 2010;Winemiller & Rose, 1992): maximum total body length (cm), spawning season length (months per year), age of female maturation (years), mean longevity (years), and fecundity (number of eggs per breeding female). We quantified parental care on an ordinal scale following Grabowska and Przybylski (2015): (1) nonguarding species that do not select spawning substrates, (2) nonguarding species that hide their broods, (3) guarding species that select spawning substrates, and (4) guarding species that spawn in nests. Species life history data were compiled from Jenkins and Burkhead (1994) and Frimpong and Angermeier (2009).
We also classified species as native or introduced from Jenkins and Burkhead (1994). Species life history data are given in Table A2 in Appendix 2.
We used nonmetric multidimensional scaling (NMS) and archetype analysis (AA) to quantify life history strategies for each observed species. First, we fit a 2-dimensional NMS ordination to log(x+1)-transformed traits data with Bray-Curtis distances.
Alternative distance measures (Euclidean, Gower) produced similar results as Bray-Curtis distances (results not shown). Second, we used AA to quantify species locations within the trilateral continuum defined by opportunistic, periodic, and equilibrium-based endpoints (i.e., archetypes) following Pecuchet et al. (2017). AA is a technique used to quantify the location of observations in multidimensional space from their distance to extreme points (Cutler & Breiman, 1994), yielding a proportional life history strategy score for each species in our analysis. This approach is conceptually appropriate because most fish species exhibit some combination of life history strategies rather than a single strategy King & McFarlane, 2003;Mims & Olden, 2012).
We then summed life history strategy scores from species presence/absence data for each site and scaled the cumulative site scores from 0 to 1 (Mims & Olden, 2012;Olden & Kennard, 2010;Pecuchet et al., 2017). This provided an index of the relative importance of opportunistic, periodic, and equilibrium-based life history strategies at each sampling site for use in statistical models described below.

| Linking life history and environmental conditions
We compiled six environmental variables, including attributes of habitat volume, land use, karst terrain, and soil type (Table 1). We estimated site elevation and upstream basin size using LiDAR-derived digital elevation models (1-m resolution) with the USGS StreamStats Batch Processing Tool version 5.03 (USGS, 2021). We calculated the percent of urban land cover and agricultural land cover in upstream watersheds from the 2019 National Land Cover Dataset (NLCD) (Yang et al., 2018). Urban land cover was calculated as the sum of all "developed" NLCD classes (categories 21, 22, 23, 24), and agricultural land cover included hay/pasture, cultivated crops, and shrubland classes (categories 52, 71, 81, 82). We calculated the percent carbonate bedrock (i.e., limestone and dolomite) within each watershed using a national karst atlas (Weary & Doctor, 2014) to index potential effects of groundwater discharge on stream temperature and F I G U R E 1 Study area within the Potomac River basin of eastern North America. Open circles show sample site locations ( Table A1 in Appendix 1) and site codes (Table 1). Sites were located on streams within the Chesapeake and Ohio Canal National Historical Park near the Potomac River. Shaded areas show physiographic regions within Maryland from west to east as the Ridge and Valley, Blue Ridge, and Piedmont (Reger & Cleaves, 2008), and the stippled areas show regions of karst geology (Weary & Doctor, 2014). The shaded region in the inset map shows the Chesapeake Bay watershed flow. We also used the STATSGO2 dataset (NRCS, 2021) to quantify the percent of soils in each watershed with the lowest infiltration rates and highest runoff potential (i.e., class D soils) (NRCS, 2007).
Several highly correlated variables (Pearson r > .7) were excluded from further analysis (e.g., percent forest cover inversely related to percent agricultural land cover).
We evaluated environmental predictors of life history strategy scores among sites from beta regression models with AIC corrected for small sample size (AICc). Beta regression is appropriate for this analysis because the response variables (life history scores) are expressed as proportional data within sites (Douma & Weedon, 2019).
We scaled environmental predictors to a mean of 0 and standard deviation of 1 to facilitate comparison of model coefficients. We then fit models using logit links for all additive combinations of environmental covariates (64 models per response variable). We evaluated AICc to rank the best models based on maximum likelihood estimation, and we considered models within 2.0 AICc units from the best model (ΔAICc) to be insignificantly different from one another (Burnham & Anderson, 2002). We used the R package "betareg" version 3-1.4 to fit beta regression models (Cribari-Neto & Zeileis, 2010) and R package "MuMIn" version 1.43.17 (Barton, 2020) to facilitate model comparisons.
We also used NMS to visualize environmental relationships with fish community composition among sites and physiographic regions.
We fit a 2-dimensional NMS ordination to log(x+1)-transformed fish abundance with Bray-Curtis distances. We then plotted environmental covariates as vectors in the ordination space and evaluated their fit to the data after 1000 permutations. We used functions "metaMDS" and "envfit" in R package "vegan" version 2.5-7 (Oksanen et al., 2020) for NMS analyses. We conducted all analyses in R version 4.1.1 (R Core Team, 2021).

| RE SULTS
Sample sites ranged in elevation 57-173 m above sea level (NAVD 88) with mean 116 m ± 9 m standard error (SE). Upstream basin areas ranged 130-40,647 ha with mean 9454 ha ± 3031 ha SE (Table 1). Agriculture was the primary nonforest land use (mean 29% of watershed area), followed by urban land cover (mean 9% of watershed area) ( Table 1). Agricultural and urban land cover were positively correlated ( Figure A1  Creek, site 20), whereas the greatest agricultural land cover was near the geographic center of the study area (an unnamed tributary near Shepherdstown WV, site 13). Class D soils (i.e., highest runoff potential) ranged from 0 to 10% of sampled watersheds, TA B L E 1 Environmental covariates for sample sites: elevation (ELE), upstream basin area (UBA), percent urban land cover (URB), percent agricultural land cover (AGR), percent limestone parent material in karst terrain (KAR), and percent soil class D (SCD) Note: Percent data are given as the percent of upstream watershed areas. Site codes area mapped in Figure 1. Unnamed tributaries are abbreviated UNT. Sites codes with * were sampled during 2018; Otherwise sites were sampled in 2019. Site location coordinates are given in Table A1 in Appendix 1. and the percent watershed area with carbonate bedrock (i.e., karst terrain) ranged from 0 to 100% (Table 1) was not strongly associated with other environmental covariates in the analysis (Spearman r < |.3|, p > .2, respectively) ( Figure A1 in Appendix 3).
We collected 3801 individuals from 51 species of which 32 species (63%) were considered native to the Potomac River basin ( Valley portion of the Potomac River basin (Albertson, 1995;Hitt et al., 2021;Welsh, 1996). Checkered sculpin was the only species observed in one site (site 13; Figure 1) and was negatively associated with abundance of other species in the dataset ( Figure A2 in Appendix 5).
Spatial variation in fish community structure was represented by a 2-dimensional NMS ordination of fish abundance data (stress = 0.10; Figure 2). Axis 1 was primarily associated with karst geology (axis loading = 1.0; Table 3) but also corresponded to agricultural and urban land cover (axis loadings = 0.63 and 0.64, respectively; Table 3). By contrast, variation along axis 2 primarily was defined by elevation, watershed area, and class D soils (axis loadings > |0.96|, respectively; Table 3). Physiographic regions varied primarily along axis 2, and fish communities in the Ridge and Valley region exhibited more spatial variation than communities from other physiographic regions ( Figure 2).
Life history traits exhibited substantial variation among study species ( A 2-dimensional NMS ordination represented interspecific variation in life history strategies (stress = 0.08; Figure 3). Axis 1 primarily indicated variation in body size and associated traits (fecundity, maturation age, longevity), and axis 2 primarily indicated a gradient between spawning season length and parental care ( Table 3)  Life history strategies were more variable within some taxonomic families than others. Each of the three cottid species in our analysis were characterized as strong equilibrium strategists (>85% equilibrium), and the five catostomid species were characterized by periodic strategies (>75% periodic; Figure 4). By contrast, other  Note: Standard error (SE) for abundance across sites is given in parentheses. Native species are indicated with an asterisk (Jenkins & Burkhead, 1994) with 2 exceptions as indicated in superscripts. Species codes are plotted in Figure 3, and species traits data are given in Table A2 in Appendix 2. a Jenkins and Burkhead (1994) classify N. leptocephalus "native but possibly introduced," and we consider it introduced. b Jenkins and Burkhead (1994) classify P. notatus "introduced but possibly native," and we consider it native.

TA B L E 2 (Continued)
F I G U R E 2 Nonmetric multidimensional scaling (NMS) ordination representing fish community structure by sites and physiographic regions. Site codes are given in Table 1, and environmental variables are represented by vectors for elevation (ELE), upstream basin area (UBA), urban land cover (URB), agricultural land cover (AGR), karst terrain (KAR), and soils with high runoff potential (SCD) model coefficients (Table 5). Basin size and urbanization were not included in the best models for any life history strategy.

| DISCUSS ION
Our Winemiller & Rose, 1992), indicating evolutionary processes that transcend zoogeographic boundaries. This is particularly noteworthy for the study area due to zoogeographic effects of Great Falls of the Potomac on fish species richness and endemism (Jenkins & Burkhead, 1994;Stauffer et al., 1995). For example, checkered sculpin, Potomac sculpin, and Blue Ridge sculpin (Cottus caeruleomentum) represented end-members for the equilibrium strategy due to their low fecundity, small body size, and investment in parental care (Figure 3). This pattern has been shown previously for freshwater sculpins (Winemiller, 2005) even though the species in our analysis are endemic to the region (Hitt et al., 2021;Kinziger et al., 2000;Robins, 1961 Note: Covariates are defined in Table 1 (fish assemblage structure) and Table 4 (life history strategy). Goodness of fit is indexed by the squared correlation coefficient (R 2 ) and empirical type-1 error rate (p) from 1000 permutation tests.

TA B L E 3
Covariate relationships to nonmetric multidimensional scaling (NMS) ordinations for fish assemblage structure ( Figure 2) and life history strategy (Figure 3)

F I G U R E 3 Nonmetric multidimensional scaling (NMS) ordination
representing fish life history diversity. Variables are represented as vectors for spawning season length (SS), fecundity (FE), longevity (LO), total length (TL), female maturation age (MA), and parental care (PC). Archetype analysis endpoints associated with periodic (PER), equilibrium (EQU), and opportunistic (OPP) strategies are shown as "X." Filled circles indicate native species. Species codes are given in Table 2, and life history data are given in Table A2 in Appendix 2 patterns with prior research. For example, Winemiller and Rose (1992) identified Gambusia sp. an exemplar of the opportunistic strategy, corresponding with our results.
Karst terrain was an important predictor of life history strategies (Table 5), indicating the importance of groundwater-surface water interactions for stream fish community composition. Groundwater depth and volume influence the thermal resiliency of stream ecosystems (Briggs et al., 2018;Hare et al., 2021;Johnson et al., 2020;Snyder et al., 2015), and streams located in karst terrain are strongly influenced by losses from the surface to aquifers and the emergence of groundwater through springs and seeps (Bonacci et al., 2009). Our analysis demonstrated that karst terrain was associated with a life history strategy that capitalizes on stable environmental conditions, suggesting a stabilizing effect of karst groundwater dynamics on stream fish habitat conditions. However, groundwater in karst terrain typically exhibits spatially and temporally complex flow and recharge dynamics rather than spatially uniform processes (Bonacci et al., 2009;Evaldi et al., 2009;Kozar et al., 1991), and this can affect streams in di-   (Figure 3) representing opportunistic (black), periodic (white), and equilibrium (grey) endpoints. Species codes are given in Table 2 F I G U R E 5 Proportional life history strategy scores across sites representing the abundance of opportunistic (black), periodic (white), and equilibrium (gray) strategists. Site codes are given in Table 1 on their chemical composition. We cannot fully account for potential differences among karst types in our study because most of the sampled streams lacked flow gages, and mainstem river gages typically underrepresent variation observed in headwater streams (Deweber et al., 2014;Kovach et al., 2019). However, one karst stream in our study area supports flow data (Antietam Creek, USGS gage 01619000), and flow in this site was less variable than in a nearby stream outside of karst terrain (Catoctin Creek, USGS gage 01637500) ( Figure A3 in Appendix 6). This finding is consistent with prior research indicating the overriding importance of fractured rock layers for groundwater flow rather than conduits or caves within the study area (Evaldi et al., 2009;Kozar et al., 1991;White, 1977) because increased rock contact area facilitates conductive heat exchange processes and moderates quickflow storm responses (Bonacci et al., 2009).
Our study also indicates the importance of soil properties and runoff processes for fish life history strategies. In contrast to karst terrain, we found that streams draining watersheds with high runoff potential were associated with opportunistic life history strategists (Table 5), suggesting the importance of an extended spawning period and short generation time to facilitate recovery from repeated disturbance events (i.e., discrete high or low flow events; Resh et al., 1988). Schlosser (1990) observed longitudinal variation in opportunistic life history strategies and attributed this to flashy flows in headwater areas versus the comparative stability of larger rivers. In contrast, we found that basin size (i.e., an index of stream volume) was less important than soil type in our best models, suggesting an overriding effect of soil properties and runoff dynamics. Hydrologic soil classification data are available globally (Ross et al., 2018), and this provides opportunities to evaluate the patterns observed here within other zoogeographic and physiographic regions.
In contrast to our expectation, nonforest land use did not increase opportunistic life history strategies. Instead, agricultural development showed no relationship to opportunistic strategies and was positively associated with equilibrium strategies. Moreover, we found no effect of urbanization in the best models, despite evidence that impervious land cover increases downstream peak flows (Anderson, 1970;O'Driscoll et al., 2010;Sauer et al., 1983) and evidence that increasing peak flows promotes opportunistic life history strategies in Potomac River fish communities . This result may be due to the spatial arrangement of our sample sites (see below) or due to moderating effects of karstic groundwater on stream ecosystem responses to land use practices. For example, Kollaus et al. (2015) attributed temporal stability of fish communities in an urbanizing landscape to moderating effects of karst terrain and associated groundwater processes.
Alternatively, our index of parental care may indicate avoidance of substrate embeddedness or other physical habitat alternations associated with agricultural development (Diana et al., 2006). For instance, bluehead chub (Nocomis leptocephalus; NOLE) exhibits high levels of parental care due to nest construction and maintenance, and this behavior enables population persistence in agricultural TA B L E 5 Top models for environmental predictors of fish life history strategies across sites (n = 20) Note: Environmental variables are defined in Table 1. Excluded variables are indicated with a dash. AICc gives the Akaike information criterion corrected for small sample size. Models with ∆AICc < 2.0 were considered to share statistical support for the best model. landscapes by clearing fine substrates from spawning areas (Hitt & Roberts, 2012;Peoples et al., 2011). We also observed this species in streams draining watersheds with extensive agricultural development (sites 14, 15, and 17), suggesting that parental care may compensate for potentially adverse environmental conditions. Likewise, checkered sculpin exhibits nest cleaning behaviors to remove fine sediments (R. Hagerty, U.S. Fish and Wildlife Service; personal communication), and this species was observed in sites with extensive agricultural development (sites 12 and 13; Table A3 in Appendix 4).
The Our use of AA demonstrated its utility for quantifying species life history as composites of disparate strategies, and this was appropriate given the mix of life history traits that most fishes exhibit King & McFarlane, 2003;Winemiller & Rose, 1992).
However, our use of AA was facilitated by the large range of life history traits among species in our dataset which permitted us to interpret meaningful end-members for each life history strategy.
For instance, eastern mosquitofish represented the opportunistic strategy, and the absence of this species in the dataset would have established an opportunistic endpoint relative to banded killifish and mimic shiner rather than the more extreme traits of eastern mosquitofish. Applications of AA therefore can enable quantitative interpretation of species life history as combinations of strategies (Pecuchet et al., 2017) but require interpretation relative to patterns observed across large geographic regions (Mims et al., 2010;Winemiller & Rose, 1992).
A central tenet in climate change research is that biological responses will be more sensitive to extreme environmental conditions than average conditions (Turner et al., 2020), and our study indicates the utility of life history theory for understanding these mechanisms (Lancaster et al., 2017). Many river systems have shown increased flow variation over recent decades (Coumou & Rahmstorf, 2012;Milly et al., 2008;Rahmstorf & Coumou, 2011;Ward et al., 2015) in response to extreme precipitation events (Easterling et al., 2000;Gershunov et al., 2019). Prior research has demonstrated the importance of scouring flows for fish population dynamics (Blum et al., 2018;Kanno et al., 2015), and our study extends this perspective to the community level through the analysis of life history traits that transcend zoogeographic boundaries. Our results also suggest that groundwater processes in karst terrain stabilize environmental conditions in receiving streams, but the sensitivity of these systems will depend in part on groundwater depth (Hare et al., 2021), spatially complex flow pathways (Kozar et al., 1991), and temporal lags in pre-

CO N FLI C T O F I NTE R E S T
The authors declare no conflicts of interest.

TA B L E A 2 (Continued)
F I G U R E A 1 Spearman correlations in environmental variables across sites. Variables are abbreviated as elevation (ELE), upstream basin area (UBA), urban land cover (URB), agricultural land cover (AGR), carbonate parent material in karst terrain (KAR), and class D soils (SCD). Land cover and geological variables are expressed as the percent of upstream basin area.
A PPE N D I X 4 TA B L E A 3 Species abundance by site. Site codes are given in Table 1, and species codes are given in Table 2 Species code

TA B L E A 3 (Continued)
A PPE N D I X 5 A PPE N D I X 6 F I G U R E A 2 Spearman correlations in species abundance across sites. Species codes are given in Table 2 and Table A1 in Appendix 1

F I G U R E A 3
Comparison of stream flow variability in karst terrain vs nonkarst terrain within the study area. The karst site is located at Antietam Creek near Waynesboro, Pennsylvania (U.S. Geological Survey gage #01619000), and the nonkarst site is located at Catoctin Creek near Middletown, Maryland (U.S. Geological Survey gage #01637500). Flow data were adjusted for upstream basin area in each site (karst site = 93.5 mi 2 ; nonkarst site = 66.9 mi 2 ). The nonkarst site exhibited greater variance in basin area-adjusted flow (Conover squared ranks test p < .0001) in this sample of over 497,000 observations from 7/1/2005 to 7/1/2020. This test statistic provides a nonparametric version of Levene's test for homogeneity of variance among groups